Shaping Professional Identity Through Professional Development: A Retrospective Study of TESOL Professionals
Bibliographic record
Abstract
In an educational milieu student learning outcomes are directly related to teacher professional identity (TPI) i.e. improvement in the TPI will bear a direct positive effect on the learners’ academic achievements. Current study focuses on the development of TPI of English as a Foreign Language Teacher at English Language Institute (ELI) of a Saudi Arabian university through an in-service Cambridge English Teachers (CET) Professional Development (PD) program (CET-PD). Five determinants of TPI - Knowledge of Teaching Context (KCT), Collegial Collaboration (CC), Teaching Practices (TPs), Teacher Self-Efficacy (TSE), and Teacher Agency (TA) were studied before and after the PD program. Retrospective pretest-posttest research design was employed for addressing the research question: whereas responses on the five determinants were elicited from 120 participants through a self-administered questionnaire before and after the CET-PD program. Due to non-normality of data, a non-parametric statistic test-Wilcoxon signed Rank test was employed to analyze the collected data using SPSS. Results of the study revealed that three determinants of TPI - KCT, TSE, and TPs exhibited larger differences; whereas, for CC the differences were moderate and for TA the differences were minimal. By and large, due to in-service CET- PD program TPI exhibited improvement. The results of the study will be beneficial for teacher trainers to focus more on the teachers’ awareness of the learners’ and institutional contextual knowledge in a culture embedded in conservative norms. This study is a part of the quantitative phase of an ongoing Ph.D. project which employs mixed method convergent design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".